Iris recognition is widely regarded as one of the most reliable biometric identifiers currently available. The accuracy of iris recognition systems is currently on par with fingerprints and, given the correct state of the art, better than facial recognition techniques. An iris pattern is unique to any individual eye: the irises of each eye are different for an individual and even between identical twins.
The majority of commercial iris recognition systems are based on a few fundamental principals. In such systems, an iris of a subject is illuminated with light from controlled and ambient light sources. A camera and the controlled light source are located at some pre-defined standoff distance from the subject. The camera, including a (possibly filtered) lens and a sensor acquire an iris image that is then captured by a computer. The iris image is then segmented (i.e., the iris portion of an image is separated from the rest of the captured image), normalized, and an iris template (commonly referred to as an iris code) is generated. The template is then matched against templates in an existing database of previously enrolled iris templates. A match against the database indicates that the iris associated with the current template is the same iris that was used to create the template that is present in the database. The camera sensor used to capture the iris image of the subject may be either a CCD or CMOS sensor.
An iris recognition system developed by Sarnoff Corporation of Princeton, N.J., known as iris on the Move™ (IOM), permits moving subjects to be identified at distances up to three meters from the iris recognition equipment. More particularly, the IOM system employs strobed Near Infrared (NIR) illumination to capture iris images. The use of NIR permits the capture of iris features with very high contrast. NIR strobed illumination freezes the motion of the subject and because the subject is illuminated for very small amounts of type (typically about 2.5 milliseconds), high illumination intensities may be employed without posing a safety hazard to the eyes of the subject. The high illumination intensities produce very bright specularities on an eye of the subject, which in turn may be used to locate an iris of the subject for coarse segmentation (i.e., a rough separation in an image of pixels that correspond to the irises of a subject).
In the past, IOM system implementations required both specialized hardware to control the capture of images and to synchronize illumination and specialized software to locate specularities. The specialized hardware was external to the camera sensor itself, which rendered the IOM system expensive. There exists systems that are less expensive than IOM that rely on visible light cell phone camera technology, however, such systems do not rely on NIR imagery and are considerably less accurate than NIR-based systems.
Accordingly, what would be desirable, but has not yet been provided, is an inexpensive, highly integrated, highly accurate iris recognition system that is adapted to employ specular reflection as an eye-finding technique and uses strobed NIR as a means for imaging irises with very bright light. It is further desirable that such a system employs coarse segmentation of the iris, autofocusing, and automatic gain control.